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Background and Objectives: Recent studies suggest that the choroid plexus (CP) may function as a site of access of inflammatory cells into the CNS in multiple sclerosis (MS). Pediatric-onset MS (POMS) is characterized by a high inflammatory burden, as evidenced by a high relapse rate and volume of T2 lesions, making patients with POMS an informative population to evaluate choroid plexus volume (CPV). The objectives of the study were (1) to evaluate CPV at symptom onset in participants with POMS compared with healthy controls (HCs); (2) to evaluate changes in CPV in the first year of disease in participants with POMS; and (3) to evaluate associations between CPV, brain volumes, relapse activity, and disability in participants with POMS., Methods: Baseline 1.5T MRI scans were acquired from 23 participants with POMS and 23 age-matched and sex-matched HCs; 18 participants with POMS also had 12-month follow-up MRI scans. The CP of the lateral ventricles was segmented manually. CP and brain structure volumes were normalized for total intracranial volume. The number of relapses, T2 and gadolinium-enhancing T1 lesion counts, and Expanded Disability Status Scale (EDSS) scores at 12 months were also analyzed. Baseline CPVs were compared between groups using the Wilcoxon exact test, and CPV change from baseline to 12 months in participants with POMS was compared using the Wilcoxon signed-rank test. The relationship between CPV and brain volumetric measures, T2 lesion volumes, lesion count, number of relapses, and EDSS scores was assessed through Spearman correlation., Results: The median normalized CPV was 1.51 × 10 -3 (interquartile range [IQR]: 1.32-1.76) in POMS baseline scans and 1.21 × 10 -3 (IQR: 1.1-1.47) in HC scans ( p = 0.001). CPV did not significantly change at 12 months in the 18 participants with POMS with follow-up scans ( p = 0.352). CPV in participants with POMS and HCs correlated with lateral ventricular volume ( p = 0.012 for both groups) but did not correlate with brain and T2 lesion volumes or lesion count at baseline, nor with relapse activity or EDSS scores at 12 months in participants with POMS., Discussion: CPV measured at baseline is greater in participants with POMS than in HCs. Baseline CPV did not predict higher disease activity or worse neurologic outcomes over 1 year. While higher CPV may be an early feature of inflammation in MS, its strong correlation with ventricular volumes could also reflect enlargement secondary to the mechanical attachment of CP to the ventricular wall.

Background: In school-age children, the myelination of the auditory radiation thalamocortical pathway is associated with the latency of auditory evoked responses, with the myelination of thalamocortical axons facilitating the rapid propagation of acoustic information. Little is known regarding this auditory system function-structure association in infants and toddlers., Methods and Participants: The present study tested the hypothesis that maturation of auditory radiation white-matter microstructure (e.g., fractional anisotropy (FA); measured using diffusion-weighted MRI) is associated with the latency of the infant auditory response (the P2m response, measured using magnetoencephalography, MEG) in a cross-sectional (N = 47, 2 to 24 months, 19 females) as well as longitudinal cohort (N = 18, 2 to 29 months, 8 females) of typically developing infants and toddlers. Of 18 longitudinal infants, 2 infants had data from 3 timepoints and 16 infants had data from 2 timepoints., Results: In the cross-sectional sample, non-linear maturation of P2m latency and auditory radiation diffusion measures were observed. Auditory radiation diffusion accounted for significant variance in P2m latency, even after removing the variance associated with age in both P2m latency and auditory radiation diffusion measures. In the longitudinal sample, latency and FA associations could be observed at the level of a single child., Conclusions: Findings provide strong support for the hypothesis that an increase in thalamocortical neural conduction velocity, due to increased axon diameter and/or myelin maturation, contributes to a decrease in the infant P2m auditory evoked response latency., Significance: Infant multimodal brain imaging identifies brain mechanisms contributing to the rapid changes in neural circuit activity during the first two years of life., (Copyright © 2024 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

In school-age children, the myelination of the auditory radiation thalamocortical pathway is associated with the latency of auditory evoked responses, with the myelination of thalamocortical axons facilitating the rapid propagation of acoustic information. Little is known regarding this auditory system function-structure association in infants and toddlers. The present study tested the hypothesis that maturation of auditory radiation white-matter microstructure (e.g., fractional anisotropy (FA); measured using diffusion-weighted MRI) is associated with the latency of the infant auditory response (P2m measured using magnetoencephalography, MEG) in a cross-sectional (2 to 24 months) as well as longitudinal cohort (2 to 29 months) of typically developing infants and toddlers. In the cross-sectional sample, non-linear maturation of P2m latency and auditory radiation diffusion measures were observed. After removing the variance associated with age in both P2m latency and auditory radiation diffusion measures, auditory radiation still accounted for significant variance in P2m latency. In the longitudinal sample, latency and FA associations could be observed at the level of a single child. Findings provide strong support for a contribution of auditory radiation white matter to rapid cortical auditory encoding processes in infants.

Resting-state alpha brain rhythms provide a foundation for basic as well as higher-order brain processes. Research suggests atypical maturation of the peak frequency of resting-state alpha activity (= PAF) in autism spectrum disorder (ASD). The present study examined resting-state alpha activity in young school-aged children, obtaining magnetoencephalographic (MEG) eyes-closed resting-state data from 47 typically developing (TD) males and 45 ASD males 6.0 to 9.3 years old. Results confirmed a higher PAF in ASD versus TD, and demonstrated that alpha power differences between groups were linked to the shift of PAF in ASD. Additionally, a higher PAF was associated with better cognitive performance in TD but not ASD. Finding thus suggested functional consequences of group differences in resting-state alpha activity., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Maturation of auditory cortex neural encoding processes was assessed in children with typical development (TD) and autism. Children 6-9 years old were enrolled at Time 1 (T1), with follow-up data obtained ~ 18 months later at Time 2 (T2), and ~ 36 months later at Time 3 (T3). Findings suggested an initial period of rapid auditory cortex maturation in autism, earlier than TD (prior to and surrounding the T1 exam), followed by a period of faster maturation in TD than autism (T1-T3). As a result of group maturation differences, post-stimulus group differences were observed at T1 but not T3. In contrast, stronger pre-stimulus activity in autism than TD was found at all time points, indicating this brain measure is stable across time., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The infant auditory system rapidly matures across the first years of life, with a primary goal of obtaining ever-more-accurate real-time representations of the external world. Our understanding of how left and right auditory cortex neural processes develop during infancy, however, is meager, with few studies having the statistical power to detect potential hemisphere and sex differences in primary/secondary auditory cortex maturation. Using infant magnetoencephalography (MEG) and a cross-sectional study design, left and right auditory cortex P2m responses to pure tones were examined in 114 typically developing infants and toddlers (66 males, 2 to 24 months). Non-linear maturation of P2m latency was observed, with P2m latencies decreasing rapidly as a function of age during the first year of life, followed by slower changes between 12 and 24 months. Whereas in younger infants auditory tones were encoded more slowly in the left than right hemisphere, similar left and right P2m latencies were observed by ∼21 months of age due to faster maturation rate in the left than right hemisphere. No sex differences in the maturation of the P2m responses were observed. Finally, an earlier left than right hemisphere P2m latency predicted better language performance in older infants (12 to 24 months). Findings indicate the need to consider hemisphere when examining the maturation of auditory cortex neural activity in infants and toddlers and show that the pattern of left-right hemisphere P2m maturation is associated with language performance., Competing Interests: Declaration of Competing Interest None., (Copyright © 2023. Published by Elsevier Inc.)

Introduction: The M50 electrophysiological auditory evoked response time can be measured at the superior temporal gyrus with magnetoencephalography (MEG) and its latency is related to the conduction velocity of auditory input passing from ear to auditory cortex. In children with autism spectrum disorder (ASD) and certain genetic disorders such as XYY syndrome, the auditory M50 latency has been observed to be elongated (slowed)., Methods: The goal of this study is to use neuroimaging (diffusion MR and GABA MRS) measures to predict auditory conduction velocity in typically developing (TD) children and children with autism ASD and XYY syndrome., Results: Non-linear TD support vector regression modeling methods accounted for considerably more M50 latency variance than linear models, likely due to the non-linear dependence on neuroimaging factors such as GABA MRS. While SVR models accounted for ~80% of the M50 latency variance in TD and the genetically homogenous XYY syndrome, a similar approach only accounted for ~20% of the M50 latency variance in ASD, implicating the insufficiency of diffusion MR, GABA MRS, and age factors alone. Biologically based stratification of ASD was performed by assessing the conformance of the ASD population to the TD SVR model and identifying a sub-population of children with unexpectedly long M50 latency., Discussion: Multimodal integration of neuroimaging data can help build a mechanistic understanding of brain connectivity. The unexplained M50 latency variance in ASD motivates future hypothesis generation and testing of other contributing biological factors., Competing Interests: TR discloses consulting/medical advisory board association with Prism Clinical Imaging, Spago Nanomedicine, Avexis Inc., Acadia Pharmaceuticals, Proteus Neurodynamics and Fieldline Inc. TR and JE also disclose intellectual property relating to use of MEG as a biomarker in ASD. JB discloses consulting activity with McGowan Associates. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Berman, Bloy, Blaskey, Jackel, Miller, Ross, Edgar and Roberts.)

Infant and young child electrophysiology studies have provided information regarding the maturation of face-encoding neural processes. A limitation of previous research is that very few studies have examined face-encoding processes in children 12-48 months of age, a developmental period characterized by rapid changes in the ability to encode facial information. The present study sought to fill this gap in the literature via a longitudinal study examining the maturation of a primary node in the face-encoding network-the left and right fusiform gyrus (FFG). Whole-brain magnetoencephalography (MEG) data were obtained from 25 infants with typical development at 4-12 months, and with follow-up MEG exams every ∼12 months until 3-4 years old. Children were presented with color images of Face stimuli and visual noise images (matched on spatial frequency, color distribution, and outer contour) that served as Non-Face stimuli. Using distributed source modeling, left and right face-sensitive FFG evoked waveforms were obtained from each child at each visit, with face-sensitive activity identified via examining the difference between the Non-Face and Face FFG timecourses. Before 24 months of age (Visits 1 and 2) the face-sensitive FFG M290 response was the dominant response, observed in the left and right FFG ∼250-450 ms post-stimulus. By 3-4 years old (Visit 4), the left and right face-sensitive FFG response occurred at a latency consistent with a face-sensitive M170 response ∼100-250 ms post-stimulus. Face-sensitive left and right FFG peak latencies decreased as a function of age (with age explaining greater than 70% of the variance in face-sensitive FFG latency), and with an adult-like FFG latency observed at 3-4 years old. Study findings thus showed face-sensitive FFG maturational changes across the first 4 years of life. Whereas a face-sensitive M290 response was observed under 2 years of age, by 3-4 years old, an adult-like face-sensitive M170 response was observed bilaterally. Future studies evaluating the maturation of face-sensitive FFG activity in infants at risk for neurodevelopmental disorders are of interest, with the present findings suggesting age-specific face-sensitive neural markers of a priori interest., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Chen, Allison, Green, Kuschner, Liu, Kim, Slinger, Mol, Chiang, Bloy, Roberts and Edgar.)

Background: At rest, 8 to 12 Hz alpha rhythms are the dominant rhythm in the brain, with a common peak alpha frequency (PAF = the frequency at which alpha generators show maximum power) observed across brain regions. Although a common PAF across brain regions should result in high between-region connectivity, especially connectivity measures assessing the phase-similarity between alpha generators, high inter-regional alpha connectivity has not been observed. The present study was conducted as an initial step toward identifying mechanisms that allow brain regions to maintain functional independence in the presence of a common PAF., Methods: MEG data were obtained from 16 healthy control male adults (mean age = 24 years; range 21 to 30 years). A task requiring participants to alternate between a 10 s eyes-closed condition and a 5 s eyes-open condition was used to drive parietal-occipital alpha generators, with the 10 s eyes-closed condition eliciting large-amplitude alpha activity and thus providing alpha measures with good signal-to-noise ratio for source localization. Alpha source-space measures were obtained using Vector-based Spatial-Temporal Analysis using L1-minimum-norm. In each participant, the four strongest parietal-occipital alpha generators were identified. Connectivity between sources was assessed via a measure of phase-based connectivity called inter-site phase clustering (ISPC)., Results: Intra-class correlations (ICC) showed very high similarity in the average PAF (=computed using all eyes-closed data) between the four alpha sources (ICC single measure = 0.88, p < 0.001). Despite a common average PAF, across participants, significant ISPC was often observed no more than that expected by chance. Examination of the alpha time course data indicated that low ISPC was often due to instantaneous changes in alpha phase (phase slips). ISPC analyses removing data with phase slips indicated that low ISPC was also due to slight continuous changes in the alpha frequency, with frequency drift more likely in non-significant than significant ISPC trials., Conclusions: The present exploratory effort suggested two processes underlying the lack of observed inter-regional alpha phase coherence that may help maintain regional functional independence even in the presence of a common PAF. In particular, although the alpha generators were observed to oscillate at the same rate on average, across time each alpha generator oscillated a little slower or faster, and about every one and a half seconds an alpha generator abruptly lost the beat. Because of this, functional independence among alpha generators (and thus brain regions) was the rule rather than the exception. Studies replicating these processes that allow brain regions to maintain functional independence, using different source localization methods and in different conditions (e.g., a true resting state), are warranted., Impact Statement: Using source localization to measure parietal-occipital alpha generator activity, two properties that limit between-region alpha functional connectivity are proposed. In particular, a model of alpha generator activity is offered where via transient phase slips occurring approximately every 1.5 s, as well as slight non-stationarity in the alpha frequency, brain regions retain a common alpha frequency while also maintaining regional identity and presumably functionality. Findings also suggest novel markers for use in studies examining changes in alpha activity across maturation as well as in studies examining alpha activity in patient populations where alpha abnormalities have been reported., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Associations between age, resting-state (RS) peak-alpha-frequency (PAF = frequency showing largest amplitude alpha activity), and thalamic volume (thalamus thought to modulate alpha activity) were examined to understand differences in RS alpha activity between children with autism spectrum disorder (ASD) and typically-developing children (TDC) noted in prior studies. RS MEG and structural-MRI data were obtained from 51 ASD and 70 TDC 6- to 18-year-old males. PAF and thalamic volume maturation were observed in TDC but not ASD. Although PAF was associated with right thalamic volume in TDC (R 2  = 0.12, p = 0.01) but not ASD (R 2  = 0.01, p = 0.35), this group difference was not large enough to reach significance. Findings thus showed unusual maturation of brain function and structure in ASD as well as an across-group thalamic contribution to alpha rhythms., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.)

Prevailing theories of the neural basis of at least a subset of individuals with autism spectrum disorder (ASD) include an imbalance of excitatory and inhibitory neurotransmission. These circuitry imbalances are commonly probed in adults using auditory steady-state responses (ASSR, driven at 40 Hz) to elicit coherent electrophysiological responses (EEG/MEG) from intact circuitry. Challenges to the ASSR methodology occur during development, where the optimal ASSR driving frequency may be unknown. An alternative approach (more agnostic to driving frequency) is the amplitude-modulated (AM) sweep in which the amplitude of a tone (with carrier frequency 500 Hz) is modulated as a sweep from 10 to 100 Hz over the course of ∼15 s. Phase synchrony of evoked responses, measured via intra-trial coherence, is recorded (by EEG or MEG) as a function of frequency. We applied such AM sweep stimuli bilaterally to 40 typically developing and 80 children with ASD, aged 6-18 years. Diagnoses were confirmed by DSM-5 criteria as well as autism diagnostic observation schedule (ADOS) observational assessment. Stimuli were presented binaurally during MEG recording and consisted of 20 AM swept stimuli (500 Hz carrier; sweep 10-100 Hz up and down) with a duration of ∼30 s each. Peak intra-trial coherence values and peak response frequencies of source modeled responses (auditory cortex) were examined. First, the phase synchrony or inter-trial coherence (ITC) of the ASSR is diminished in ASD; second, hemispheric bias in the ASSR, observed in typical development (TD), is maintained in ASD, and third, that the frequency at which the peak response is obtained varies on an individual basis, in part dependent on age, and with altered developmental trajectories in ASD vs. TD. Finally, there appears an association between auditory steady-state phase synchrony (taken as a proxy of neuronal circuitry integrity) and clinical assessment of language ability/impairment. We concluded that (1) the AM sweep stimulus provides a mechanism for probing ASSR in an unbiased fashion, during developmental maturation of peak response frequency, (2) peak frequencies vary, in part due to developmental age, and importantly, (3) ITC at this peak frequency is diminished in ASD, with the degree of ITC disturbance related to clinically assessed language impairment., Competing Interests: TR declares equity in Prism Clinical Imaging and Proteus Neurodynamics. He serves as a consultant/medical advisory board member for CTF, Ricoh, Spago Nanomedicine, Avexis and Acadia Pharmaceuticals. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Roberts, Bloy, Liu, Ku, Blaskey and Jackel.)

Background: 47,XYY syndrome (XYY) is a male sex chromosome disorder where subjects have one X chromosome and two copies of the Y chromosome. XYY is associated with a physical phenotype and carries increased risk of neurodevelopmental disorders such as autism spectrum disorder (ASD). Imbalance of excitation and inhibition has been proposed as a putative biological basis of disorders such as ASD [1-3] and several studies have reported atypical brain γ-aminobutyric acid (GABA) levels in this population. Given the male preponderance in the prevalence of ASD, the unique presence of the Y chromosome in males leads to the intriguing possibility of investigating boys with XYY syndrome as a model of excess Y-chromosome genes., Method: In this study, we investigated the associations of genotype and clinical phenotype with levels of GABA, estimated by regionally localized edited magnetic resonance spectroscopy in boys with 47, XYY syndrome compared to age-matched typically developing (XY) peers., Results: Overall, we observed a decrease in GABA levels in XYY vs. XY, which appeared more significant in the left compared to the right hemisphere. There was no additional significant modulation of GABA levels in XYY according to presence/absence of ASD diagnosis. Interestingly, a positive correlation between bilateral GABA levels and testosterone levels was observed in pubescent XY boys that was not observed in XYY., Conclusion: The inhibitory neurotransmitter GABA appears to be reduced in boys with 47,XYY, especially in the left hemisphere. Further, the typical association between GABA and testosterone levels, observed in older typically developing control boys was not evident in boys with 47,XYY., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Little is known about the neural processes associated with attending to social stimuli during infancy and toddlerhood. Using infant magnetoencephalography (MEG), fusiform gyrus (FFG) activity while processing Face and Non-Face stimuli was examined in 46 typically developing infants 3 to 24 months old (28 males). Several findings indicated FFG maturation throughout the first two years of life. First, right FFG responses to Face stimuli decreased as a function of age. Second, hemispheric specialization to the face stimuli developed somewhat slowly, with earlier right than left FFG peak activity most evident after 1 year of age. Right FFG activity to Face stimuli was of clinical interest, with an earlier right FFG response associated with better performance on tests assessing social and cognitive ability. Building on the above, clinical studies examining maturational change in FFG activity (e.g., lateralization and speed) in infants at-risk for childhood disorders associated with social deficits are of interest to identify atypical FFG maturation before a formal diagnosis is possible., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Neuroimaging research on individuals who have autism spectrum disorder (ASD) has historically been limited primarily to those with age-appropriate cognitive and language performance. Children with limited abilities are frequently excluded from such neuroscience research given anticipated barriers like tolerating the loud sounds associated with magnetic resonance imaging and remaining still during data collection. To better understand brain function across the full range of ASD there is a need to (1) include individuals with limited cognitive and language performance in neuroimaging research (non-sedated, awake) and (2) improve data quality across the performance range. The purpose of this study was to develop, implement, and test the feasibility of a clinical/behavioral and technical protocol for obtaining magnetoencephalography (MEG) data. Participants were 38 children with ASD (8-12 years) meeting the study definition of minimally verbal/nonverbal language. MEG data were obtained during a passive pure-tone auditory task., Results: Based on stakeholder feedback, the MEG Protocol for Low-language/cognitive Ability Neuroimaging (MEG-PLAN) was developed, integrating clinical/behavioral and technical components to be implemented by an interdisciplinary team (clinicians, behavior specialists, scientists, and technologists). Using MEG-PLAN, a 74% success rate was achieved for acquiring MEG data, with a 71% success rate for evaluable and analyzable data. Exploratory analyses suggested nonverbal IQ and adaptive skills were related to reaching the point of acquirable data. No differences in group characteristics were observed between those with acquirable versus evaluable/analyzable data. Examination of data quality (evaluable trial count) was acceptable. Moreover, results were reproducible, with high intraclass correlation coefficients for pure-tone auditory latency., Conclusions: Children who have ASD who are minimally verbal/nonverbal, and often have co-occurring cognitive impairments, can be effectively and comfortably supported to complete an electrophysiological exam that yields valid and reproducible results. MEG-PLAN is a protocol that can be disseminated and implemented across research teams and adapted across technologies and neurodevelopmental disorders to collect electrophysiology and neuroimaging data in previously understudied groups of individuals.

Functional brain markers that can inform research on brain abnormalities, and especially those ready to facilitate clinical work on such abnormalities, will need to show not only considerable sensitivity and specificity but enough consistency with respect to developmental course that their validity in individual cases can be trusted. A challenge to establishing such markers may be individual differences in developmental course. The present study examined auditory cortex activity in children at an age when developmental changes to the auditory cortex 50 ms (M50) and 100 ms (M100) components are prominent to better understand the use of auditory markers in pediatric clinical research. MEG auditory encoding measures (auditory evoked fields in response to pure tone stimuli) were obtained from 15 typically developing children 6-8 years old, with measures repeated 18 and 36 months after the initial exam. MEG analyses were conducted in source space (i.e., brain location), with M50 and M100 sources identified in left and right primary/secondary auditory cortex (Heschl's gyrus). A left and right M50 response was observed at all times (Time 1, Time 2, Time 3), with M50 latency (collapsing across hemisphere) at Time 3 (77 ms) 10 ms earlier than Time 1 (87 ms; p < 0.001) and with M50 responses on average (collapsing across time) 5 ms earlier in the right (80 ms) than left hemisphere (85 ms; p < 0.05). In the majority of children, however, M50 latency changes were not constant across the three-year period; for example, whereas in some children a ~10 ms latency reduction was observed from Time 1 to Time 2, in other children a ~10 ms latency reduction was observed from Time 2 to Time 3. M100 responses were defined by a significant "peak" of detected power with magnetic field topography opposite M50 and occurring 50-100 ms later than the M50. Although M100s were observed in a few children at Time 1 and Time 2 (and more often in the right than left hemisphere), M100s were not observed in the majority of children except in the right hemisphere at Time 3. In sum, longitudinal findings showed large between- and within-subject variability in rate of change as well as time to reach neural developmental milestones (e.g., presence of a detectable M100 response). Findings also demonstrated the need to examine whole-brain activity, given hemisphere differences in the rate of auditory cortex maturation. Pediatric research will need to take such normal variability into account when seeking clinical auditory markers., (Copyright © 2020 Edgar, Blaskey, Green, Konka, Shen, Dipiero, Berman, Bloy, Liu, McBride, Ku, Kuschner, Airey, Kim, Franzen, Miller and Roberts.)

This multimodal imaging study used magnetoencephalography, diffusion magnetic resonance imaging (MRI), and gamma-aminobutyric acid (GABA) magnetic resonance spectroscopy (MRS) to identify and contrast the multiple physiological mechanisms associated with auditory processing efficiency in typically developing (TD) children and children with autism spectrum disorder (ASD). Efficient transmission of auditory input between the ear and auditory cortex is necessary for rapid encoding of auditory sensory information. It was hypothesized that the M50 auditory evoked response latency would be modulated by white matter microstructure (indexed by diffusion MRI) and by tonic inhibition (indexed by GABA MRS). Participants were 77 children diagnosed with ASD and 40 TD controls aged 7-17 years. A model of M50 latency with auditory radiation fractional anisotropy and age as independent variables was able to predict 52% of M50 latency variance in TD children, but only 12% of variance in ASD. The ASD group exhibited altered patterns of M50 latency modulation characterized by both higher variance and deviation from the expected structure-function relationship established with the TD group. The TD M50 latency model was used to identify a subpopulation of ASD who are significant "outliers" to the TD model. The ASD outlier group exhibited unexpectedly long M50 latencies in conjunction with significantly lower GABA levels. These findings indicate the dependence of electrophysiologic sensory response latency on underlying microstructure (white matter) and neurochemistry (synaptic activity). This study demonstrates the use of biologically based measures to stratify ASD according to their brain-level "building blocks" as an alternative to their behavioral phenotype. LAY SUMMARY: Children with ASD often have a slower brain response when hearing sounds. This study used multiple brain imaging techniques to examine the structural and neurochemical factors which control the brain's response time to auditory tones in children with ASD and TD children. The relationship between brain imaging measures and brain response time was also used to identify ASD subgroups. Autism Res 2020, 13: 1730-1745. © 2020 International Society for Autism Research and Wiley Periodicals LLC., (© 2020 International Society for Autism Research and Wiley Periodicals LLC.)

An additional Y chromosome occurs in ~1 in 1,000 males, resulting in the karyotype 47,XYY. The phenotype includes tall stature, hypotonia, neuropsychiatric comorbidities, and an increased risk of infertility in adulthood. Little is known about testicular function in childhood and adolescence in 47,XYY. This cross-sectional study aimed to assess testicular function serum biomarkers, including total testosterone, inhibin B, and anti-mullerian hormone (AMH), in 82 boys with XYY (11.3 ± 3.8 years) compared with 66 male controls (11.6 ± 3.8 years). The association of testicular hormones with physical features, neuropsychological phenotype, and magnetoencephalography (MEG) was assessed with multiple linear regression models. Results indicate males with XYY have significantly lower inhibin B (median 84 pg/ml vs. 109 pg/ml, p = .004) and higher AMH (median 41 ng/ml vs. 29 ng/ml, p = .011); however, testosterone, testicular volume, and stretched penile length were not different from controls. In the exploratory analysis of relationships between hormone concentrations and phenotypic assessments, higher inhibin B concentrations were positively correlated with lower BMI and better cognitive, academic, and behavioral outcomes in the XYY group. Testosterone concentrations were positively associated with better behavioral outcomes in boys with XYY. Higher testosterone and inhibin B concentrations were also associated with shorter auditory latencies measured using magnetoencephalography (MEG) in XYY. With a few exceptions, testicular hormones were not associated with phenotypic outcomes in controls. In conclusion, there is evidence of subtle impaired testicular function in boys with XYY and a newly described relationship between measures of testicular function and some aspects of the XYY phenotype., (© 2020 Wiley Periodicals LLC.)

Autism spectrum disorder (ASD) is primarily characterized by impairments in social communication and the appearance of repetitive behaviors with restricted interests. Increasingly, evidence also points to a general deficit of motor tone and coordination in children and adults with ASD; yet the neural basis of motor functional impairment in ASD remains poorly characterized. In this study, we used magnetoencephalography (MEG) to (1) assess potential group differences between typically developing (TD) and ASD participants in motor cortical oscillatory activity observed on a simple button-press task and (2) to do so over a sufficiently broad age-range so as to capture age-dependent changes associated with development. Event-related desynchronization was evaluated in Mu (8-13 Hz) and Beta (15-30 Hz) frequency bands (Mu-ERD, Beta-ERD). In addition, post-movement Beta rebound (PMBR), and movement-related gamma (60-90 Hz) synchrony (MRGS) were also assessed in a cohort of 123 participants (63 typically developing (TD) and 59 with ASD) ranging in age from 8 to 24.9 years. We observed significant age-dependent linear trends in Beta-ERD and MRGS power with age for both TD and ASD groups; which did not differ significantly between groups. However, for PMBR, in addition to a significant effect of age, we also observed a significant reduction in PMBR power in the ASD group (p < 0.05). Post-hoc tests showed that this omnibus group difference was driven by the older cohort of children >13.2 years (p < 0.001) and this group difference was not observed when assessing PMBR activity for the younger PMBR groups (ages 8-13.2 years; p = 0.48). Moreover, for the older ASD cohort, hierarchical regression showed a significant relationship between PMBR activity and clinical scores of ASD severity (Social Responsiveness Scale (SRS T scores)), after regressing out the effect of age (p < 0.05). Our results show substantial age-dependent changes in motor cortical oscillations (Beta-ERD and MRGS) occur for both TD and ASD children and diverge only for PMBR, and most significantly for older adolescents and adults with ASD. While the functional significance of PMBR and reduced PMBR signaling remains to be fully elucidated, these results underscore the importance of considering age as a factor when assessing motor cortical oscillations and group differences in children with ASD., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Several electrophysiological parameters, including the auditory evoked response component M50/M100 latencies and the phase synchrony of transient and steady-state gamma-band oscillations have been implicated as atypical (to various extents) in autism spectrum disorder (ASD). Furthermore, some hypotheses suggest that an underlying neurobiological mechanism for these observations might be atypical local circuit function indexed by atypical levels of inhibitory neurotransmitter, GABA. This study was a randomized, placebo-controlled, double-blind, escalating-dose, acute investigation conducted in 25 14-18 year-old adolescents with ASD. The study assessed the sensitivity of magnetoencephalography (MEG) and MEGAPRESS "GABA" magnetic resonance spectroscopy (MRS) to monitor dose-dependent acute effects, as well as seeking to define properties of the pre-drug "baseline" electrophysiological and GABA signatures that might predict responsiveness to the GABA-B agonist, arbaclofen (STX-209). Overall, GABA levels and gamma-band oscillatory activity showed no acute changes at either low (15 mg) or high (30 mg) dose. Evoked M50 response latency measures tended to shorten (normalize), but there was heterogeneity across the group in M50 latency response, with only a subset of participants ( n = 6) showing significant M50 latency shortening, and only at the 15 mg dose. Findings thus suggest that MEG M50 latency measures show acute effects of arbaclofen administration in select individuals, perhaps reflecting effective target engagement. Whether these subjects have a greater trend towards clinical benefit remains to be established. Finally, findings also provide preliminary support for the use of objective electrophysiological measures upon which to base inclusion for optimal enrichment of populations to be included in full-scale clinical trials of arbaclofen., (Copyright © 2019 Roberts, Bloy, Blaskey, Kuschner, Gaetz, Anwar, Ku, Dipiero, Bennett and Edgar.)

We describe a unique male with a dicentric Y chromosome whose phenotype was compared to that of males with 47,XYY (XYY). The male Y-chromosome aneuploidy XYY is associated with physical, behavioral/cognitive phenotypes, and autism spectrum disorders. We hypothesize that increased risk for these phenotypes is caused by increased copy number/overexpression of Y-encoded genes. Specifically, an extra copy of the neuroligin gene NLGN4Y might elevate the risk of autism in boys with XYY. We present a unique male with the karyotype 46,X,idic(Y)(q11.22), which includes duplication of the Y short arm and proximal long arm and deletion of the distal long arm, evaluated his physical, behavioral/cognitive, and neuroimaging/magnetoencephalography (MEG) phenotypes, and measured blood RNA expression of Y genes. The proband had tall stature and cognitive function within the typical range, without autism features. His blood RNA showed twofold increase in expression of Yp genes versus XY controls, and absent expression of deleted Yq genes, including NLGN4Y. The M100 latencies were similar to findings in typically developing males. In summary, the proband had overexpression of a subset of Yp genes, absent NLGN4Y expression, without ASD findings or XYY-MEG latency findings. These results are consistent with a role for NLGN4Y overexpression in the etiology of behavioral phenotypes associated with XYY. Further investigation of NLGN4Y as an ASD risk gene in XYY is warranted. The genotype and phenotype(s) of this subject may also provide insight into how Y chromosome genes contribute to normal male development and the male predominance in ASD., (© 2019 Wiley Periodicals, Inc.)

Objective: Resective surgery is the most effective treatment option for patients with refractory epilepsy; however identification of patients who will benefit from epilepsy surgery remains challenging. Synthetic aperture magnetometry and excess kurtosis mapping (SAM(g2)) of magnetoencephalography (MEG) is a non-invasive tool that warrants further examination in the pediatric epilepsy population. Here, we examined the utility of MEG with SAM(g2) to determine if MEG epileptiform foci correlates with surgical outcome and to develop a predictive model incorporating MEG information to best assess likelihood of seizure improvement/freedom from resective surgery., Methods: 564 subjects who had MEG at the Children's Hospital of Philadelphia between 2010-2015 were screened. Clinical epilepsy history and prior electrographic records were extracted and reviewed and correlated with MEG findings. MEG assessments were made by both a neurologist and neuroradiologist. Predictive models were developed to assess the utility of MEG in determining Engel class at one year and five years after resective epilepsy surgery., Results: The number of MEG spike foci was highly associated with Engel class outcome at both one year and five years; however, using MEG data in isolation was not significantly predictive of 5 year surgical outcome. When combined with clinical factors; scalp EEG (single ictal onset zone), MRI (lesional or not), age and sex in a logistic regression model MEG foci was significant for Engel class outcome at both 1 year (p = 0.03) and 5 years (0.02). The percent correctly classified for Engel class at one year was 78.43% and the positive predictive value was 71.43., Significance: MEG using SAM(g2) analysis in an important non-invasive tool in the identification of those patients who will benefit most from surgery. Integrating MEG data analysis into pre-surgical evaluation can help to predict epilepsy outcome after resective surgery in the pediatric population if utilized with skilled interpretation., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Abnormal auditory neuromagnetic M50 and M100 responses, reflecting primary/secondary auditory cortex processing, have been reported in children who have autism spectrum disorder (ASD). Some studies have reported an association between delays in these responses and language impairment. However, as most prior research has focused on verbal individuals with ASD without cognitive impairment, rather little is known about neural activity during auditory processing in minimally verbal or nonverbal children who have ASD (ASD-MVNV)-children with little or no speech and often significant cognitive impairment. To understand the neurophysiological mechanisms underlying auditory processing in ASD-MVNV children, magnetoencephalography (MEG) measured M50 and M100 responses arising from left and right superior temporal gyri during tone stimuli in three cohorts: (1) MVNV children who have ASD (ASD-MVNV), (2) verbal children who have ASD and no intellectual disability (ASD-V), and (3) typically developing (TD) children. One hundred and five participants (8-12 years) were included in the final analyses (ASD-MVNV: n  = 16, 9.85 ± 1.32 years; ASD-V: n  = 55, 10.64 ± 1.31 years; TD: n  = 34, 10.18 ± 1.36 years). ASD-MVNV children showed significantly delayed M50 and M100 latencies compared to TD. These delays tended to be greater than the corresponding delays in verbal children with ASD. Across cohorts, delayed latencies were associated with language and communication skills, assessed by the Vineland Adaptive Behavior Scale Communication Domain. Findings suggest that auditory cortex neural activity measures could be dimensional objective indices of language impairment in ASD for either diagnostic (e.g., via threshold or cutoff) or prognostic (considering the continuous variable) use., Competing Interests: Competing interestsDr. Roberts declares consulting/advisory board relationships with Prism Clinical Imaging, CTF, Ricoh, Spago Nanomedical and Avexis. Additionally, he and Dr. Edgar disclose intellectual property related to MEG as a biomarker for pharmaceutical therapy, under license to MEGIN. All other authors declare no competing interests.

Age-related changes in resting-state (RS) neural rhythms in typically developing children (TDC) but not children with autism spectrum disorder (ASD) suggest that RS measures may be of clinical use in ASD only for certain ages. The study examined this issue via assessing RS peak alpha frequency (PAF), a measure previous studies, have indicated as abnormal in ASD. RS magnetoencephalographic (MEG) data were obtained from 141 TDC (6.13-17.70 years) and 204 ASD (6.07-17.93 years). A source model with 15 regional sources projected the raw MEG surface data into brain source space. PAF was identified in each participant from the source showing the largest amplitude alpha activity (7-13 Hz). Given sex differences in PAF in TDC (females > males) and relatively few females in both groups, group comparisons were conducted examining only male TDC (N = 121) and ASD (N = 183). Regressions showed significant group slope differences, with an age-related increase in PAF in TDC (R 2  = 0.32) but not ASD (R 2  = 0.01). Analyses examining male children below or above 10-years-old (median split) indicated group effects only in the younger TDC (8.90 Hz) and ASD (9.84 Hz; Cohen's d = 1.05). In the older ASD, a higher nonverbal IQ was associated with a higher PAF. In the younger TDC, a faster speed of processing was associated with a higher PAF. PAF as a marker for ASD depends on age, with a RS alpha marker of more interest in younger versus older children with ASD. Associations between PAF and cognitive ability were also found to be age and group specific., (© 2019 Wiley Periodicals, Inc.)

This study introduces an objective neurophysiological marker of language ability, the integral of event-related desynchronization in the 5-20 Hz band during 0.2-1 seconds post auditory stimulation with interleaved word/non-word tokens. This measure correlates with clinical assessment of language function in both ASD and neurotypical pediatric populations. The measure does not appear related to general cognitive ability nor autism symptom severity (beyond degree of language impairment). We suggest that this oscillatory brain activity indexes lexical search and thus increases with increased search in the mental lexicon. While specificity for language impairment in ASD remains to be determined, such an objective index has potential utility in low functioning individuals with ASD and young children during language acquisition.

Abnormal auditory discrimination neural processes, indexed by mismatch fields (MMFs) recorded by magnetoencephalography (MEG), have been reported in verbal children with ASD. Association with clinical measures indicates that delayed MMF components are associated with poorer language and communication performance. At present, little is known about neural correlates of language and communication skills in extremely language impaired (minimally-verbal/non-verbal) children who have ASD: ASD-MVNV. It is hypothesized that MMF delays observed in language-impaired but nonetheless verbal children with ASD will be exacerbated in ASD-MVNV. The present study investigated this hypothesis, examining MMF responses bilaterally during an auditory oddball paradigm with vowel stimuli in ASD-MVNV, in a verbal ASD cohort without cognitive impairment and in typically developing (TD) children. The verbal ASD cohort without cognitive impairment was split into those demonstrating considerable language impairment (CELF core language index <85; "ASD-LI") versus those with less or no language impairment (CELF CLI >85; "ASD-V"). Eighty-four participants (8-12 years) were included in final analysis: ASD-MVNV: n = 9, 9.67 ± 1.41 years, ASD: n = 48, (ASD-V: n = 27, 10.55 ± 1.21 years, ASD-LI: n = 21, 10.67 ± 1.20 years) and TD: n = 27, 10.14 ± 1.38 years. Delayed MMF latencies were found bilaterally in ASD-MVNV compared to verbal ASD (both ASD-V and ASD-LI) and TD children. Delayed MMF responses were associated with diminished language and communication skills. Furthermore, whereas the TD children showed leftward lateralization of MMF amplitude, ASD-MVNV and verbal ASD (ASD-V and ASD-LI) showed abnormal rightward lateralization. Findings suggest delayed auditory discrimination processes and abnormal rightward laterality as objective markers of language/communication skills in both verbal and MVNV children who have ASD. Autism Res 2019, 12: 1225-1235. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Brain imaging showed abnormal auditory discrimination processes in minimally-verbal/non-verbal children (MVNV) who have autism spectrum disorder (ASD). Delays in auditory discrimination were associated with impaired language and communication skills. Findings suggest these auditory neural measures may be objective markers of language and communication skills in both verbal and, previously-understudied, MVNV children who have ASD., (© 2019 International Society for Autism Research, Wiley Periodicals, Inc.)

47,XYY syndrome (XYY) is a male sex chromosome disorder where individuals have an X chromosome and two copies of the Y chromosome. XYY is associated with a physical phenotype and carries increased risk of neurodevelopmental disorders such as autism spectrum disorder (ASD). Latencies of auditory evoked responses measured by magnetoencephalography have shown atypical prolongations in several neuropsychiatric and genetic disorders; specifically, delayed auditory responses have been observed in ASD. In this study, we investigated the associations of genotype and clinical phenotype with auditory processing. Whole cortex magnetoencephalography recorded during a passive auditory paradigm (500 Hz tones) was used to assess the auditory evoked response in three groups of male children: idiopathic ASD, typically developing, and XYY boys. Response waveforms were computed for left and right auditory cortex and latencies of the ∼50 ms (M50) and ∼100 ms (M100) components were determined. M50 latencies were significantly delayed compared with typically developing controls in children with ASD in the right hemisphere only, and in children with XYY in the left hemisphere only, irrespective of whether they met diagnostic criteria for ASD. Findings on the later M100 component trended in the same directions but did not attain significance, due to increased variance. Replicating previous findings, decreased M50 and M100 latencies with age were observed bilaterally. Overall, while XYY shares an electrophysiological phenotype (delayed evoked response latency) with idiopathic ASD, the hemispheric differences warrant further investigation.

The auditory mismatch field (MMF) is a pre-attentive processing component, reflecting neural discrimination and inhibitory processing. Abnormal MMFs have been reported in children with autism spectrum disorder (ASD) along with an association with abnormal language comprehension; however, relatively little is known about MMF abnormalities to contrasting vowel stimuli in adults with ASD. To better understand the neurophysiological mechanisms underlying auditory language discrimination of vowel stimuli in individuals with ASD, magnetoencephalography was used to measure MMFs during an auditory oddball paradigm with vowel stimuli (/a/ and /u/) in adults with ASD. MMFs arising from left and right superior temporal gyrus are reported from nine high-functioning right handed males with ASD (22.22 ± 5.74yrs) and sixteen typically developing (TD) right handed males (27.25 ± 6.63yrs). The MMF was delayed in adults with ASD (188.90 ± 5.8 ms) as compared to the TD participants (173.08 ± 4.31 ms, p < 0.05). Replicating previous findings in children, the earlier M100 component to single stimulus tokens was also delayed in adults with ASD (108.59 ± 4.1 ms) compared to the TD participants (94.60 ± 3.0 ms, p < 0.05). However, there was no correlation between delayed M100 latency and MMF latency. Furthermore, whereas TD participants showed a leftward lateralization of MMF amplitude, participants with ASD showed an opposite (rightward) lateralization. Findings suggest that adults with ASD have hemispherically- and temporally- abnormal auditory discrimination processing in addition to and distinct from abnormal neurophysiological mechanisms in earlier cortical responses., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The M50 and M100 auditory evoked responses reflect early auditory processes in the primary/secondary auditory cortex. Although previous M50 and M100 studies have been conducted on individuals with autism spectrum disorder (ASD) and indicate disruption of encoding simple sensory information, analogous investigations of the neural correlates of auditory processing through development from children into adults are very limited. Magnetoencephalography was used to record signals arising from the left and right superior temporal gyrus during auditory presentation of tones to children/adolescents and adults with ASD as well as typically developing (TD) controls. One hundred and thirty-two participants (aged 6-42 years) were included into the final analyses (children/adolescents: TD, n = 36, 9.21 ± 1.6 years; ASD, n = 58, 10.07 ± 2.38 years; adults: TD, n = 19, 26.97 ± 1.29 years; ASD, n = 19, 23.80 ± 6.26 years). There were main effects of group on M50 and M100 latency (p < 0.001) over hemisphere and frequency. Delayed M50 and M100 latencies were found in participants with ASD compared to the TD group, and earlier M50 and M100 latencies were associated with increased age. Furthermore, there was a statistically significant association between language ability and both M50 and M100 latencies. Importantly, differences in M50 and M100 latencies between TD and ASD cohorts, often reported in children, persisted into adulthood, with no evidence supporting latency convergence., (© 2020 S. Karger AG, Basel.)

47,XYY syndrome (XYY) is one of the common forms of sex chromosome aneuploidy in males. XYY males tend to have tall stature, early speech, motor delays, social and behavioral challenges, and a high rate of language impairment. Recent studies indicate that 20-40% of males with XYY meet diagnostic criteria for autism spectrum disorder (ASD; the rate in the general population is 1-2%). Although many studies have examined the neural correlates of language impairment in ASD, few similar studies have been conducted on individuals with XYY. Studies using magnetoencephalography (MEG) in idiopathic ASD (ASD-I) have demonstrated delayed neurophysiological responses to changes in the auditory stream, revealed in the mismatch negativity or its magnetic counterpart, the mismatch field (MMF). This study investigated whether similar findings are observed in XYY-associated ASD and whether delayed processing is also present in individuals with XYY without ASD. MEG measured MMFs arising from the left and the right superior temporal gyrus during an auditory oddball paradigm with vowel stimuli (/a/ and /u/) in children/adolescents with XYY both with and without a diagnosis of ASD, as well as in those with ASD-I and in typically developing controls (TD). Ninety male participants (6-17 years old) were included in the final analyses (TD, n = 38, 11.50 ± 2.88 years; ASD-I, n = 21, 13.83 ± 3.25 years; XYY without ASD, n = 15, 12.65 ± 3.91 years; XYY with ASD, n = 16, 12.62 ± 3.19 years). The groups did not differ significantly in age (p > 0.05). There was a main effect of group on MMF latency (p < 0.001). Delayed MMF latencies were found in participants with XYY both with and without an ASD diagnosis, as well as in the ASD-I group compared to the TD group (ps < 0.001). Furthermore, participants with XYY (with and without ASD) showed a longer MMF latency than the ASD-I group (ps < 0.001). There was, however, no significant difference in MMF latency between individuals with XYY with ASD and those with XYY without ASD. Delayed MMF latencies were associated with severity of language impairment. Our findings suggest that auditory MMF latency delays are pronounced in this specific Y chromosome aneuploidy disorder, both with and without an ASD diagnosis, and thus may implicate the genes of the Y chromosome in mediating atypical MMF activity., (© 2019 S. Karger AG, Basel.)

Brain networks based on resting state connectivity as well as inter-regional anatomical pathways obtained using diffusion imaging have provided insight into pathology and development. Such work has underscored the need for methods that can extract sub-networks that can accurately capture the connectivity patterns of the underlying population while simultaneously describing the variation of sub-networks at the subject level. We have designed a multi-layer graph clustering method that extracts clusters of nodes, called 'network hubs', which display higher levels of connectivity within the cluster than to the rest of the brain. The method determines an atlas of network hubs that describes the population, as well as weights that characterize subject-wise variation in terms of within- and between-hub connectivity. This lowers the dimensionality of brain networks, thereby providing a representation amenable to statistical analyses. The applicability of the proposed technique is demonstrated by extracting an atlas of network hubs for a population of typically developing controls (TDCs) as well as children with autism spectrum disorder (ASD), and using the structural and functional networks of a population to determine the subject-level variation of these hubs and their inter-connectivity. These hubs are then used to compare ASD and TDCs. Our method is generalizable to any population whose connectivity (structural or functional) can be captured via non-negative network graphs., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Autism spectrum disorder (ASD) is hypothesized to arise from imbalances between excitatory and inhibitory neurotransmission (E/I imbalance). Studies have demonstrated E/I imbalance in individuals with ASD and also corresponding rodent models. One neural process thought to be reliant on E/I balance is gamma-band activity (Gamma), with support arising from observed correlations between motor, as well as visual, Gamma and underlying GABA concentrations in healthy adults. Additionally, decreased Gamma has been observed in ASD individuals and relevant animal models, though the direct relationship between Gamma and GABA concentrations in ASD remains unexplored. This study combined magnetoencephalography (MEG) and edited magnetic resonance spectroscopy (MRS) in 27 typically developing individuals (TD) and 30 individuals with ASD. Auditory cortex localized phase-locked Gamma was compared to resting Superior Temporal Gyrus relative cortical GABA concentrations for both children/adolescents and adults. Children/adolescents with ASD exhibited significantly decreased GABA+/Creatine (Cr) levels, though typical Gamma. Additionally, these children/adolescents lacked the typical maturation of GABA+/Cr concentrations and gamma-band coherence. Furthermore, children/adolescents with ASD additionally failed to exhibit the typical GABA+/Cr to gamma-band coherence association. This altered coupling during childhood/adolescence may result in Gamma decreases observed in the adults with ASD. Therefore, individuals with ASD exhibit improper local neuronal circuitry maturation during a childhood/adolescence critical period, when GABA is involved in configuring of such circuit functioning. Provocatively a novel line of treatment is suggested (with a critical time window); by increasing neural GABA levels in children/adolescents with ASD, proper local circuitry maturation may be restored resulting in typical Gamma in adulthood. Autism Res 2017, 10: 593-607. © 2016 International Society for Autism Research, Wiley Periodicals, Inc., (© 2016 International Society for Autism Research, Wiley Periodicals, Inc.)

Background: Individuals with autism spectrum disorder (ASD) show atypical brain activity, perhaps due to delayed maturation. Previous studies examining the maturation of auditory electrophysiological activity have been limited due to their use of cross-sectional designs. The present study took a first step in examining magnetoencephalography (MEG) evidence of abnormal auditory response maturation in ASD via the use of a longitudinal design., Methods: Initially recruited for a previous study, 27 children with ASD and nine typically developing (TD) children, aged 6- to 11-years-old, were re-recruited two to five years later. At both timepoints, MEG data were obtained while participants passively listened to sinusoidal pure-tones. Bilateral primary/secondary auditory cortex time domain (100 ms evoked response latency (M100)) and spectrotemporal measures (gamma-band power and inter-trial coherence (ITC)) were examined. MEG measures were also qualitatively examined for five children who exhibited "optimal outcome", participants who were initially on spectrum, but no longer met diagnostic criteria at follow-up., Results: M100 latencies were delayed in ASD versus TD at the initial exam (~ 19 ms) and at follow-up (~ 18 ms). At both exams, M100 latencies were associated with clinical ASD severity. In addition, gamma-band evoked power and ITC were reduced in ASD versus TD. M100 latency and gamma-band maturation rates did not differ between ASD and TD. Of note, the cohort of five children that demonstrated "optimal outcome" additionally exhibited M100 latency and gamma-band activity mean values in-between TD and ASD at both timepoints. Though justifying only qualitative interpretation, these "optimal outcome" related data are presented here to motivate future studies., Conclusions: Children with ASD showed perturbed auditory cortex neural activity, as evidenced by M100 latency delays as well as reduced transient gamma-band activity. Despite evidence for maturation of these responses in ASD, the neural abnormalities in ASD persisted across time. Of note, data from the five children whom demonstrated "optimal outcome" qualitatively suggest that such clinical improvements may be associated with auditory brain responses intermediate between TD and ASD. These "optimal outcome" related results are not statistically significant though, likely due to the low sample size of this cohort, and to be expected as a result of the relatively low proportion of "optimal outcome" in the ASD population. Thus, further investigations with larger cohorts are needed to determine if the above auditory response phenotypes have prognostic utility, predictive of clinical outcome.

Background: An understanding of the maturation of auditory cortex responses in typically developing infants and toddlers is needed to later identify auditory processing abnormalities in infants at risk for neurodevelopmental disorders. The availability of infant and young child magnetoencephalography (MEG) systems may now provide near optimal assessment of left and right hemisphere auditory neuromagnetic responses in young populations. To assess the performance of a novel whole-head infant MEG system, a cross-sectional study examined the maturation of left and right auditory cortex responses in children 6- to 59-months of age., Methods: Blocks of 1000 Hz (1st and 3rd blocks) and 500 Hz tones (2nd block) were presented while MEG data were recorded using an infant/young child biomagnetometer (Artemis 123). Data were obtained from 29 children (11 males; 6- to 59-months). Latency measures were obtained for the first positive-to-negative evoked response waveform complex in each hemisphere. Latency and age associations as well as frequency and hemisphere latency differences were examined. For the 1000 Hz tone, measures of reliability were computed., Results: For the first response-a response with a "P2m" topography-latencies decreased as a function of age. For the second response-a response with a "N2m" topography-no N2m latency and age relationships were observed. A main effect of tone frequency showed earlier P2m responses for 1st 1000 Hz (150 ms) and 2nd 1000 Hz (148 ms) vs. 500 Hz tones (162 ms). A significant main effect of hemisphere showed earlier N2m responses for 2nd 1000 Hz (226 ms) vs. 1st 1000 Hz (241 ms) vs. 500 Hz tones (265 ms). P2m and N2m interclass correlation coefficient latency findings were as follows: left P2m (0.72, p < 0.001), right P2m (0.84, p < 0.001), left N2m (0.77, p < 0.001), and right N2m (0.77,p < 0.01)., Conclusions: Findings of strong age and latency associations, sensitivity to tone frequency, and good test-retest reliability support the viability of longitudinal infant MEG studies that include younger as well as older participants as well as studies examining auditory processing abnormalities in infants at risk for neurodevelopmental disorders.

Alpha circuits (8-12 Hz), necessary for basic and complex brain processes, are abnormal in autism spectrum disorder (ASD). The present study obtained estimates of resting-state (RS) alpha activity in children with ASD and examined associations between alpha activity, age, and clinical symptoms. Given that the thalamus modulates cortical RS alpha rhythms, associations between thalamic structure and alpha activity were examined. RS magnetoencephalography was obtained from 47 typically-developing children (TDC) and 41 children with ASD. RS alpha activity was measured using distributed source localization. Left and right thalamic volume measurements were also obtained. In both groups, the strongest alpha activity was observed in Calcarine Sulcus regions. In Calcarine regions, only TDC showed the expected association between age and alpha peak frequency. ASD had more alpha activity than TDC in regions bordering the Central Sulcus as well as parietal association cortices. In ASD, whereas greater left Central Sulcus relative alpha activity was associated with higher Social Responsiveness Scale (SRS) scores, greater Calcarine region relative alpha activity was associated with lower SRS scores. Although thalamic volume group differences were not observed, relationships between thalamic volume and Calcarine alpha power were unique to TDC. The present study also identified a failure to shift peak alpha frequency as a function of age in primary alpha-generating areas in children with ASD. Findings suggested that increased RS alpha activity in primary motor and somatosensory as well as parietal multimodal areas-with increased alpha thought to reflect greater inhibition-might impair the ability to identify or interpret social cues. Finally, to our knowledge, this is the first study to report associations between thalamic volume and alpha power, an association observed only in TDC. The lack of thalamic and alpha associations in ASD suggests thalamic contributions to RS alpha abnormalities in ASD.

Adult studies have shown that a basic property of resting-state (RS) brain activity is the coupling of posterior alpha oscillations (alpha phase) to posterior gamma oscillations (gamma amplitude). The present study examined whether this basic RS process is present in children. Given reports of abnormal parietal-occipital RS alpha in children with autism spectrum disorder (ASD), the present study examined whether RS alpha-to-gamma phase-amplitude coupling (PAC) is disrupted in ASD. Simulations presented in this study showed limitations with traditional PAC analyses. In particular, to avoid false-positive PAC findings, simulations showed the need to use a unilateral passband to filter the upper frequency band as well as the need for longer epochs of data. For the human study, eyes-closed RS magnetoencephalography data were analyzed from 25 children with ASD and 18 typically developing (TD) children with at least 60 sec of artifact-free data. Source modeling provided continuous time course data at a midline parietal-occipital source for PAC analyses. Greater alpha-to-gamma PAC was observed in ASD than TD (p<0.005). Although children with ASD had higher PAC values, in both groups gamma activity increased at the peak of the alpha oscillation. In addition, an association between alpha power and alpha-to-gamma PAC was observed in both groups, although this relationship was stronger in ASD than TD (p<0.05). Present results demonstrated that although alpha-to-gamma PAC is present in children, this basic RS process is abnormal in children with ASD. Finally, simulations and the human data highlighted the need to consider the interplay between alpha power, epoch length, and choice of signal processing methods on PAC estimates.

Examination of resting state brain activity using electrophysiological measures like complexity as well as functional connectivity is of growing interest in the study of autism spectrum disorders (ASD). The present paper jointly examined complexity and connectivity to obtain a more detailed characterization of resting state brain activity in ASD. Multi-scale entropy was computed to quantify the signal complexity, and synchronization likelihood was used to evaluate functional connectivity (FC), with node strength values providing a sensor-level measure of connectivity to facilitate comparisons with complexity. Sensor level analysis of complexity and connectivity was performed at different frequency bands computed from resting state MEG from 26 children with ASD and 22 typically developing controls (TD). Analyses revealed band-specific group differences in each measure that agreed with other functional studies in fMRI and EEG: higher complexity in TD than ASD, in frontal regions in the delta band and occipital-parietal regions in the alpha band, and lower complexity in TD than in ASD in delta (parietal regions), theta (central and temporal regions) and gamma (frontal-central boundary regions); increased short-range connectivity in ASD in the frontal lobe in the delta band and long-range connectivity in the temporal, parietal and occipital lobes in the alpha band. Finally, and perhaps most strikingly, group differences between ASD and TD in complexity and FC appear spatially complementary, such that where FC was elevated in ASD, complexity was reduced (and vice versa). The correlation of regional average complexity and connectivity node strength with symptom severity scores of ASD subjects supported the overall complementarity (with opposing sign) of connectivity and complexity measures, pointing to either diminished connectivity leading to elevated entropy due to poor inhibitory regulation or chaotic signals prohibiting effective measure of connectivity.

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by wide range of symptoms and severity including domains such as language impairment (LI). This study aims to create a quantifiable marker of ASD and a stratification marker for LI using multimodality imaging data that can handle missing data by including subjects that fail to complete all the aspects of a multimodality imaging study, obviating the need to remove subjects with incomplete data, as is done by conventional methods., Methods: An ensemble of classifiers with several subsets of complete data is employed. The outputs from such subset classifiers are fused using a weighted aggregation giving an aggregate probabilistic score for each subject. Such fusion classifiers are created to obtain a marker for ASD and to stratify LI using three categories of features, two extracted from separate auditory tasks using magnetoencephalography (MEG) and the third extracted from diffusion tensor imaging (DTI)., Results: A clear distinction between ASD and neurotypical controls (5-fold accuracy of 83.3% and testing accuracy of 87%) and between ASD/+LI and ASD/-LI (5-fold accuracy of 70.1% and testing accuracy of 61.1%) was obtained. One of the MEG features, mismatch field (MMF) latency contributed the most to group discrimination, followed by DTI features from superior temporal white matter and superior longitudinal fasciculus as determined by feature ranking., Comparison With Existing Methods: Higher classification accuracy was achieved in comparison with single modality classifiers., Conclusion: This methodology can be readily applied in large studies where high percentage of missing data is expected., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Background: A major motivation in designing the new infant and child magnetoencephalography (MEG) system described in this manuscript is the premise that electrophysiological signatures (resting activity and evoked responses) may serve as biomarkers of neurodevelopmental disorders, with neuronal abnormalities in conditions such as autism spectrum disorder (ASD) potentially detectable early in development. Whole-head MEG systems are generally optimized/sized for adults. Since magnetic field produced by neuronal currents decreases as a function of distance(2) and infants and young children have smaller head sizes (and thus increased brain-to-sensor distance), whole-head adult MEG systems do not provide optimal signal-to-noise in younger individuals. This spurred development of a whole-head infant and young child MEG system - Artemis 123., Methods: In addition to describing the design of the Artemis 123, the focus of this manuscript is the use of Artemis 123 to obtain auditory evoked neuromagnetic recordings and resting-state data in young children. Data were collected from a 14-month-old female, an 18-month-old female, and a 48-month-old male. Phantom data are also provided to show localization accuracy., Results: Examination of Artemis 123 auditory data showed generalizability and reproducibility, with auditory responses observed in all participants. The auditory MEG measures were also found to be manipulable, exhibiting sensitivity to tone frequency. Furthermore, there appeared to be a predictable sensitivity of evoked components to development, with latencies decreasing with age. Examination of resting-state data showed characteristic oscillatory activity. Finally, phantom data showed that dipole sources could be localized with an error less than 0.5 cm., Conclusions: Artemis 123 allows efficient recording of high-quality whole-head MEG in infants four years and younger. Future work will involve examining the feasibility of obtaining somatosensory and visual recordings in similar-age children as well as obtaining recordings from younger infants. Thus, the Artemis 123 offers the promise of detecting earlier diagnostic signatures in such neurodevelopmental disorders.

(1)H magnetic resonance spectroscopy ((1)H MRS) and spectral editing methods, such as MEGA-PRESS, allow researchers to investigate metabolite and neurotransmitter concentrations in-vivo. Here we address the utilization of (1)H MRS for the investigation of GABA concentrations in the ASD brain, in three locations; motor, visual and auditory areas. An initial repeatability study (5 subjects, 5 repeated measures separated by ~5days on average) indicated no significant effect of reference metabolite choice on GABA quantitation (p>0.6). Coefficients of variation for GABA+/NAA, GABA+/Cr and GABA+/Glx were all of the order of 9-11%. Based on these findings, we investigated creatine-normalized GABA+ ratios (GABA+/Cr) in a group of (N=17) children with autism spectrum disorder (ASD) and (N=17) typically developing children (TD) for Motor, Auditory and Visual regions of interest (ROIs). Linear regression analysis of gray matter (GM) volume changes (known to occur with development) revealed a significant decrease of GM volume with Age for Motor (F(1,30)=17.92; p<0.001) and Visual F(1,16)=14.41; p<0.005 but not the Auditory ROI (p=0.55). Inspection of GABA+/Cr changes with Age revealed a marginally significant change for the Motor ROI only (F(1,30)=4.11; p=0.054). Subsequent analyses were thus conducted for each ROI separately using Age and GM volume as covariates. No group differences in GABA+/Cr were observed for the Visual ROI between TD vs. ASD children. However, the Motor and Auditory ROI showed significantly reduced GABA+/Cr in ASD (Motor p<0.05; Auditory p<0.01). The mean deficiency in GABA+/Cr from the Motor ROI was approximately 11% and Auditory ROI was approximately 22%. Our novel findings support the model of regional differences in GABA+/Cr in the ASD brain, primarily in Auditory and to a lesser extent Motor but not Visual areas., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Connectivity analysis of resting state brain has provided a novel means of investigating brain networks in the study of neurodevelpmental disorders. The study of functional networks, often represented by high dimensional graphs, predicates on the ability of methods in succinctly extracting meaningful representative connectivity information at the subject and population level. This need motivates the development of techniques that can extract underlying network modules that characterize the connectivity in a population, while capturing variations of these modules at the individual level. In this paper, we propose a multi-layer raph clustering technique that fuses the information from a collection of connectivity networks of a population to extract the underlying common network modules that serve as network hubs for the population. These hubs form a functional network atlas. In addition, our technique provides subject-specific factors designed to characterize and quantify the degree of intra- and inter- connectivity between hubs, thereby providing a representation that is amenable to group level statistical analyses. We demonstrate the utility of the technique by creating a population network atlas of connectivity by examining MEG based functional connectivity in typically developing children, and using this to describe the individualized variation in those diagnosed with autism spectrum disorder.

The gamma-band response is thought to represent a key neural signature of information processing in the human brain. These brain signals have been associated with a variety of sensory modalities (vision, sensation, and audition) and also following basic motor responses, yet the functional significance of the motor gamma-band response remains unclear. We used the Multi-Source Interference Task (MSIT) to assess the sensitivity of these cortical motor gamma-band rhythms to stimuli producing response interference. We recorded MEG from adult participants (N=24) during MSIT task performance and compared motor gamma-band activity on Control and Interference trials. Reaction time on MSIT Interference trials was significantly longer (~0.2 s) for all subjects. Response interference produced a significant increase in motor gamma-band activity including ~0.5 s sustained increase in gamma-band activity from contralateral primary motor area directly preceding the response. In addition, activation of increased right Inferior Frontal Gyrus (R-IFG) was observed at gamma-band frequencies ~0.2 s prior to the button press response. Post-hoc analysis of R-IFG gamma-band activity was observed to correlate with reaction time increases to response interference. Our study is the first to record MEG during MSIT task performance. We observed novel activity of the motor gamma-band on interference trials which was sustained prior to the response and in novel locations including contralateral (BA6), and R-IFG. Our results support the idea that R-IFG is specialized structure for response control that also functions at gamma-band frequencies. Together, these data provide evidence for a motor gamma-band network for response selection and maintenance of planned behavior., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Most diffusion imaging studies have used subject registration to an atlas space for enhanced quantification of anatomy. However, standard diffusion tensor atlases lack information in regions of fiber crossing and are based on adult anatomy. The degree of error associated with applying these atlases to studies of children for example has not yet been estimated but may lead to suboptimal results. This paper describes a novel technique for generating population-specific high angular resolution diffusion imaging (HARDI)-based atlases consisting of labeled regions of homogenous white matter. Our approach uses a fiber orientation distribution (FOD) diffusion model and a data driven clustering algorithm. White matter regional labeling is achieved by our automated data driven clustering algorithm that has the potential to delineate white matter regions based on fiber complexity and orientation. The advantage of such an atlas is that it is study specific and more comprehensive in describing regions of white matter homogeneity as compared to standard anatomical atlases. We have applied this state of the art technique to a dataset consisting of adolescent and preadolescent children, creating one of the first examples of a HARDI-based atlas, thereby establishing the feasibility of the atlas creation framework. The white matter regions generated by our automated clustering algorithm have lower FOD variance than when compared to the regions created from a standard anatomical atlas., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Connectivity matrices obtained from various modalities (DTI, MEG and fMRI) provide a unique insight into brain processes. Their high dimensionality necessitates the development of methods for population-based statistics, in the face of small sample sizes. In this paper, we present such a method applicable to functional connectivity networks, based on identifying the basis of dominant connectivity components that characterize the patterns of brain pathology and population variation. Projection of individual connectivity matrices into this basis allows for dimensionality reduction, facilitating subsequent statistical analysis. We find dominant components for a collection of connectivity matrices by using the projective non-negative component analysis technique which ensures that the components have non-negative elements and are non-negatively combined to obtain individual subject networks, facilitating interpretation. We demonstrate the feasibility of our novel framework by applying it to simulated connectivity matrices as well as to a clinical study using connectivity matrices derived from resting state magnetoencephalography (MEG) data in a population of subjects diagnosed with autism spectrum disorder (ASD).

Pathologies like autism and schizophrenia are a broad set of disorders with multiple etiologies in the same diagnostic category. This paper presents a method for unsupervised cluster analysis using multi-edge similarity graphs that combine information from different modalities. The method alleviates the issues with traditional supervised classification methods that use diagnostic labels and are therefore unable to exploit or elucidate the underlying heterogeneity of the dataset under analysis. The framework introduced in this paper has the ability to employ diverse features that define different aspects of pathology obtained from different modalities to create a multi-edged graph on which clustering is performed. The weights on the multiple edges are optimized using a novel concept of 'holding power' that describes the certainty with which a subject belongs to a cluster. We apply the technique to two separate clinical populations of autism spectrum disorder (ASD) and schizophrenia (SCZ), where the multi-edged graph for each population is created by combining information from structural networks and cognitive scores. For the ASD-control population the method clusters the data into two classes and the SCZ-control population is clustered into four. The two classes in ASD agree with underlying diagnostic labels with 92% accuracy and the SCZ clustering agrees with 78% accuracy, indicating a greater heterogeneity in the SCZ population.

Structural connectivity models hold great promise for expanding what is known about the ways information travels throughout the brain. The physiologic interpretability of structural connectivity models depends heavily on how the connections between regions are quantified. This article presents an integrated structural connectivity framework designed around such an interpretation. The framework provides three measures to characterize the structural connectivity of a subject: (1) the structural connectivity matrix describing the proportion of connections between pairs of nodes, (2) the nodal connection distribution (nCD) characterizing the proportion of connections that terminate in each node, and (3) the connection density image, which presents the density of connections as they traverse through white matter (WM). Individually, each possesses different information concerning the structural connectivity of the individual and could potentially be useful for a variety of tasks, ranging from characterizing and localizing group differences to identifying novel parcellations of the cortex. The efficiency of the proposed framework allows the determination of large structural connectivity networks, consisting of many small nodal regions, providing a more detailed description of a subject's connectivity. The nCD provides a gray matter contrast that can potentially aid in investigating local cytoarchitecture and connectivity. Similarly, the connection density images offer insight into the WM pathways, potentially identifying focal differences that affect a number of pathways. The reliability of these measures was established through a test/retest paradigm performed on nine subjects, while the utility of the method was evaluated through its applications to 20 diffusion datasets acquired from typically developing adolescents.

The paper presents a method for learning multimodal classifiers from datasets in which not all subjects have data from all modalities. Usually, subjects with a severe form of pathology are the ones failing to satisfactorily complete the study, especially when it consists of multiple imaging modalities. A classifier capable of handling subjects with unequal numbers of modalities prevents discarding any subjects, as is traditionally done, thereby broadening the scope of the classifier to more severe pathology. It also allows design of the classifier to include as much of the available information as possible and facilitates testing of subjects with missing modalities over the constructed classifier. The presented method employs an ensemble based approach where several subsets of complete data are formed and trained using individual classifiers., The output from these classifiers is fused using a weighted aggregation step giving an optimal probabilistic score for each subject. The method is applied to a spatio-temporal dataset for autism spectrum disorders (ASD) (96 patients with ASD and 42 typically developing controls) that consists of functional features from magnetoencephalography (MEG) and structural connectivity features from diffusion tensor imaging (DTI). A clear distinction between ASD and controls is obtained with an average 5-fold accuracy of 83.3% and testing accuracy of 88.4%. The fusion classifier performance is superior to the classification achieved using single modalities as well as multimodal classifier using only complete data (78.3%). The presented multimodal classifier framework is applicable to all modality combinations.

This paper presents a paradigm for generating a quantifiable marker of pathology that supports diagnosis and provides a potential biomarker of neuropsychiatric disorders, such as autism spectrum disorder (ASD). This is achieved by creating high-dimensional nonlinear pattern classifiers using support vector machines (SVM), that learn the underlying pattern of pathology using numerous atlas-based regional features extracted from diffusion tensor imaging (DTI) data. These classifiers, in addition to providing insight into the group separation between patients and controls, are applicable on a single subject basis and have the potential to aid in diagnosis by assigning a probabilistic abnormality score to each subject that quantifies the degree of pathology and can be used in combination with other clinical scores to aid in diagnostic decision. They also produce a ranking of regions that contribute most to the group classification and separation, thereby providing a neurobiological insight into the pathology. As an illustrative application of the general framework for creating diffusion based abnormality classifiers we create classifiers for a dataset consisting of 45 children with ASD (mean age 10.5 ± 2.5 yr) as compared to 30 typically developing (TD) controls (mean age 10.3 ± 2.5 yr). Based on the abnormality scores, a distinction between the ASD population and TD controls was achieved with 80% leave one out (LOO) cross-validation accuracy with high significance of p<0.001, ~84% specificity and ~74% sensitivity. Regions that contributed to this abnormality score involved fractional anisotropy (FA) differences mainly in right occipital regions as well as in left superior longitudinal fasciculus, external and internal capsule while mean diffusivity (MD) discriminates were observed primarily in right occipital gyrus and right temporal white matter., (Copyright © 2011 Elsevier Inc. All rights reserved.)

The paper presents a method for creating abnormality classifiers from high angular resolution diffusion imaging (HARDI) data. We utilized the fiber orientation distribution (FOD) diffusion model to represent the local WM architecture of each subject. The FOD images are then spatially normalized to a common template using a non-linear registration technique. Regions of homogeneous white matter architecture (ROIs) are determined by applying a parcellation algorithm to the population average FOD image. Orientation invariant features of each ROI's mean FOD are determined and concatenated into a feature vector to represent each subject. Principal component analysis (PCA) was used for dimensionality reduction and a linear support vector machine (SVM) classifier is trained on the PCA coefficients. The classifier assigns each test subject a probabilistic score indicating the likelihood of belonging to the patient group. The method was validated using a 5 fold validation scheme on a population containing autism spectrum disorder (ASD) patients and typically developing (TD) controls. A clear distinction between ASD patients and controls was obtained with a 77% accuracy.

This work presents an automated method for partitioning neuronal white matter (WM) into regions of interest with uniform WM architecture. These regions can then be used to replace atlas-derived regions for any subsequent statistical analysis. The fiber orientation distribution function is used as a model of WM architecture resulting in a voxel similarity function sensitive to both fiber orientations and configurations. The method utilizes the normalized cuts algorithm to partition WM voxels based on this similarity function along with a connected component labeling algorithm to ensure spatial compactness. We illustrate the algorithms ability to discern regions based on both orientation and complexity through its application to a simulated fiber crossing and an in-vivo dataset.